Relapsed acute myeloid leukemia (relAML) remains a clinical challenge. We have shown that epigenetic heterogeneity may contribute to transcriptional dysregulation and disease progression in AML, but the specific aberrant transcriptional programs have not been identified. We analyzed molecular profiles from patient-matched diagnostic and relapse AML specimens. A subset of differentially expressed genes (DEG) that were disparate in direction of expression change identified 2 patient subtypes. We predicted that transcriptional regulators (TR) might regulate the expression patterns observed. The expression patterns of the top TR predicted for the disparate genes associated with clinical outcomes. The top TR predicted for the disparate DEG and DEG identified in a patient-derived xenograft model of relAML included members of the LIM domain only 2 - LIM domain binding 1 - TAL BHLH TF1, erythroid differentiation factor (LMO2-LDB1-TAL1) multisubunit complex (LTMC). Analysis of DepMap data identified LMO2-dependent cells with a subset highly expressing TAL1, suggesting coordinated regulation. TAL1 copurified in immunoprecipitation for LMO2 and LDB1 followed by tandem mass spectrometry analysis in HEL and K562 cells, and results from chromatin immunoprecipitation experiments suggest significant co-occupancy of TAL1 and LDB1. Loss-of-function experiments targeting LMO2, LDB1, and TAL1 in AML cell lines associated with reduced cell growth, downregulation of cell cycle genes, and a negative association with gene expression patterns observed in relapsed patients with increased TAL1 expression. Our results from primary AML specimens and functional analyses of AML cell lines supports an essential role for the LTMC in AML. Targeting the complex or downstream effectors could provide novel therapeutic considerations for a subset of patients with AML.

We report two unrelated adults with homozygous (P1) or compound heterozygous (P2) private loss-of-function variants of V-Rel Reticuloendotheliosis Viral Oncogene Homolog B ( RELB). The resulting deficiency of functional RelB impairs the induction of NFKB2 mRNA and NF-κB2 (p100/p52) protein by lymphotoxin in the fibroblasts of the patients. These defects are rescued by transduction with wild-type RELB complementary DNA (cDNA). By contrast, the response of RelB-deficient fibroblasts to Tumor Necrosis Factor (TNF) or IL-1β via the canonical NF-κB pathway remains intact. P1 and P2 have low proportions of naïve CD4 + and CD8 + T cells and of memory B cells. Moreover, their naïve B cells cannot differentiate into immunoglobulin G (IgG)- or immunoglobulin A (IgA)-secreting cells in response to CD40L/IL-21, and the development of IL-17A/F-producing T cells is strongly impaired in vitro. Finally, the patients produce neutralizing autoantibodies against type I interferons (IFNs), even after hematopoietic stem cell transplantation, attesting to a persistent dysfunction of thymic epithelial cells in T cell selection and central tolerance to some autoantigens. Thus, inherited human RelB deficiency disrupts the alternative NF-κB pathway, underlying a T- and B cell immunodeficiency, which, together with neutralizing autoantibodies against type I IFNs, confers a predisposition to viral, bacterial, and fungal infections.

Relapsed acute myeloid leukemia (AML) remains a clinical challenge with patients suffering from poor clinical outcomes. To date, studies have not found specific recurrent somatic events that explain disease relapse in most patients. We have previously shown that epigenetic heterogeneity may contribute to transcriptional dysregulation and disease progression in AML but the specific transcriptional programs that drive disease relapse have not been identified. To characterize the transcriptional landscapes in relapsed AML, we analyzed multi-omics molecular profiles from two cohorts of patient-matched diagnostic and relapse AML specimens (cohorts I: n = 29 and II: n = 30). We identified 5,416 differentially expressed genes (DEGs) between diagnosis and relapse in cohort I. The majority of these DEGs did not associate with DNA methylation changes at their respective promoters. Unsupervised clustering of the DEGs identified two transcriptomic subtypes characterized by a subset of DEGs that were disparate in direction of expression change in the two subtypes. These subtypes were not significantly associated with specific somatic events or evolution patterns between diagnosis and relapse. Similar differential expression patterns and patient clusters were observed in Cohort II. We utilized Binding Analysis for Regulation of Transcription (PMID: 29608647) to computationally predict transcriptional regulators (TRs) that might regulate the disparate gene expression patterns observed. The expression patterns of the top 30 TRs predicted for the disparate genes associated with clinical outcomes in the TCGA and BEAT AML patient cohorts (Advanced Expression Survival Analysis [PMID: 31607216]; p < 0.02). Functional annotation of the top TRs predicted for the disparate genes was notable for transcription factors (TFs) known to regulate hematopoiesis, including members of the LIM domain Only 2 (LMO2) multi-subunit complex (TAL transcription Factor 1 [TAL1], GATA binding protein 1 [GATA1], and LIM domain binding protein 1 [LDB1]). A mouse xenograft model of AML relapse was used to generate gene expression data from the human malignant cells. DEGs were identified between engrafted and post-chemotherapy treated AML cells. BART analysis on the DEGs also identified LMO2/LDB1/LMO2 complex members as potential TRs. The LMO2/LDB1/TAL1 complex is known to function in hematopoiesis and has been shown to have an oncogenic role in T-cell acute lymphoblastic leukemia, where the complex has been shown to enforce a stem cell phenotype in T-cell progenitor cells. However, a functional role for it in relapsed AML has not been defined. We hypothesized that this complex is an oncogenic TR in AML relapse. Analysis of DepMap (https://depmap.org/portal) results in AML cell lines identified LMO2-dependent cells. A subset of these cell lines harbored high expression of TAL1, suggesting coordinated regulation. To confirm interactions between LMO2/LDB1/TAL1 complex members, we performed immunoprecipitation for LMO2 and LDB1 followed by tandem mass spectrometry analysis of binding proteins in HEL and K562 cells. TAL1, Transcription Factor 12, and other known complex members co-purified with LMO2 and LDB1. Loss of function experiments targeting LMO2, TAL1, and LDB1 in these AML cell lines altered gene expression and reduced growth (t-test p < 0.05). Functional analyses of the DEGs identified in the in vitro experiments suggested that loss of function associated with downregulation of cell cycle checkpoints, MYC, and MYC target genes (Normalized enrichment score [NES] < -1.5, q < 0.05). Accordingly, we observed upregulation of cell cycle and MYC gene sets in the patient-matched AML specimens with increased TAL1 expression at relapse (NES > 1.5, q < 0.05). Importantly, overall changes in expression acquired with LMO2 and LDB1 loss of function inversely correlated with DEGs in relapsed patients with higher TAL1 expression (NES < -1.5, q < 0.05). Our data from primary AML specimens and functional analyses in AML cell lines supports an essential role for the LMO2/LDB1/TAL1 complex, especially in AML relapsed disease. The macromolecular protein complex plays a role in the maintenance of hematopoietic stem cells, a role that may be co-opted in AML. Targeting the complex or its downstream effectors could be a novel therapeutic consideration for relapsed AML patients.

Severe defects in human IFNγ immunity predispose individuals to both Bacillus Calmette-Guérin disease and tuberculosis, whereas milder defects predispose only to tuberculosis1. Here we report two adults with recurrent pulmonary tuberculosis who are homozygous for a private loss-of-function TNF variant. Neither has any other clinical phenotype and both mount normal clinical and biological inflammatory responses. Their leukocytes, including monocytes and monocyte-derived macrophages (MDMs) do not produce TNF, even after stimulation with IFNγ. Blood leukocyte subset development is normal in these patients. However, an impairment in the respiratory burst was observed in granulocyte-macrophage colony-stimulating factor (GM-CSF)-matured MDMs and alveolar macrophage-like (AML) cells2 from both patients with TNF deficiency, TNF- or TNFR1-deficient induced pluripotent stem (iPS)-cell-derived GM-CSF-matured macrophages, and healthy control MDMs and AML cells differentiated with TNF blockers in vitro, and in lung macrophages treated with TNF blockers ex vivo. The stimulation of TNF-deficient iPS-cell-derived macrophages with TNF rescued the respiratory burst. These findings contrast with those for patients with inherited complete deficiency of the respiratory burst across all phagocytes, who are prone to multiple infections, including both Bacillus Calmette-Guérin disease and tuberculosis3. Human TNF is required for respiratory-burst-dependent immunity to Mycobacterium tuberculosis in macrophages but is surprisingly redundant otherwise, including for inflammation and immunity to weakly virulent mycobacteria and many other infectious agents.

Abstract Most cell–cell interactions and crosstalks are mediated by ligand–receptor interactions. The advent of single-cell RNA-sequencing (scRNA-seq) techniques has enabled characterizing tissue heterogeneity at single-cell level. In the past few years, several methods have been developed to study ligand–receptor interactions at cell type level using scRNA-seq data. However, there is still no easy way to query the activity of a specific user-defined signaling pathway in a targeted way or to map the interactions of the same subunit with different ligands as part of different receptor complexes. Here, we present DiSiR, a fast and easy-to-use permutation-based software framework to investigate how individual cells are interacting with each other by analyzing signaling pathways of multi-subunit ligand-activated receptors from scRNA-seq data, not only for available curated databases of ligand–receptor interactions, but also for interactions that are not listed in these databases. We show that, when utilized to infer ligand–receptor interactions from both simulated and real datasets, DiSiR outperforms other well-known permutation-based methods, e.g. CellPhoneDB and ICELLNET. Finally, to demonstrate DiSiR’s utility in exploring data and generating biologically relevant hypotheses, we apply it to COVID lung and rheumatoid arthritis (RA) synovium scRNA-seq datasets and highlight potential differences between inflammatory pathways at cell type level for control versus disease samples.

Background: Acute myeloid leukemia in patients over the age of 60 (aAML) is associated with poor prognosis. aAML patients are the majority diagnosed but are underrepresented in large molecular studies. We have identified two clinical subgroups of aAML patients with distinct survival outcomes (low-risk and high-risk) in ECOG-ACRIN Cancer Research Group's clinical trial E3999 (NCT00046930). We hypothesize that these two groups are characterized by distinct biological mechanisms that contribute to leukemogenesis. We also hypothesize that the low-risk group harbor molecular and phenotypic signatures characteristic of known better-risk AMLs. Methods: Diagnostic specimens were obtained from patients enrolled in NCT00046930. Disease enriched cells were isolated by negative selection of lymphocytes (magnetic beads). Flow cytometry was used to characterize the blast population. Bulk RNA-sequencing was performed on 220 blast enriched samples and 10 age matched normal controls (CD34+ bone marrow cells). Transcriptional differences were determined using DESeq2. Differentially expressed genes (DEGs) were identified as those with an absolute log2 fold change greater than 1 and q less than 0.05. Gene set enrichment analysis (GSEA) was performed against the MSigDB databases. Upstream regulators associated with gene expression changes were identified using Ingenuity Pathway Analysis (IPA). DESeq2 was used to identify genes that were differentially associated with overall survival times between the risk groups. Enrichment for transcription factor gene targets was calculated using EnrichR based on the CHEA Transcription Factor Target Dataset. Cytokines were quantified in a subset of patient serum samples using a Luminex assay. Results: We identified 2314 DEGs between the low-risk and high-risk aAMLs with high-risk as the baseline. The upregulated genes in the low-risk aAMLs were positively enriched for gene signatures derived from: 1. Favorable risk AML ( NPM1 mutated), 2. M4 and M5 AML patients, 3. Differentiated hematopoietic cells and 4. Inflammatory response pathways. On the contrary, upregulated genes in the high-risk aAMLs were enriched for gene signatures identified in hematopoietic and leukemic stem cells and known poor-risk AMLs (for example: EVI1 fusion). Accordingly, immunophenotypic data from flow cytometry results gated on the blast populations validated differences in the surface expression of hematopoietic cell markers between the two groups. Next, we sought to determine upstream regulators associated with the DEGs using IPA. We identified 107 potential upstream regulators that associated with the changes in gene expression observed between the low- and high-risk groups (87 activated and 20 inhibited). The results suggested that several pro-inflammatory cytokines (ex. tumor necrosis factor alpha (TNFα) and interferon gamma (IFNγ)) were predicted activators in the low-risk aAML group. Accordingly, we detected significantly higher levels of TNFα and IFNγ in the serum levels of a subset of low-risk aAML patients. Finally, we assessed for genes whose expression significantly associated with overall survival. Interestingly, in agreement with a previously proposed inflammation score (iScore), we identified higher iScore associated with the high-risk group. Of note, the upstream regulators identified do not overlap with those contributing to the calculation of iScore. Additionally, longer overall survival times were associated with higher levels of expression of genes associated with heme metabolism and erythroblast differentiation in the low-risk aAML patient group. Conclusions: Our results suggest that the low-risk aAML patients were characterized by a more mature hematopoietic cell gene expression signature and cell surface markers as well as a pro-inflammatory state. Our study supports the possibility that pro-inflammatory cytokines and/or signaling could mediate AML cell survival in the low-risk aAML patient group. The high-risk aAML patients were characterized by a more primitive hematopoietic and leukemic stem cell gene expression signature. Collectively, we propose that differences in the underlying molecular and/or immune-based mechanisms could contribute to leukemogenesis in the two risk groups. These findings suggest that distinct therapeutic approaches may need to be considered to improve clinical outcomes in the two aAML risk groups.

The purpose of this study is to identify key regulatory pathways that potentially drive abnormal gene expression program in relapsed Acute Myeloid Leukemia (AML) patients, by integrative computational analyses on multi-omics molecular profiles. Relapsed AML remains a clinical challenge. Epigenetic heterogeneity may contribute to transcriptional dysregulation and disease progression in AML. However, what specific transcriptional programs and potential regulatory mechanisms contribute to disease relapse are not yet well understood. To characterize the global transcriptional landscapes in relapsed AML, we integrated genomics data from two cohorts of matched diagnosis and relapse patient specimens. We identified 5,416 differentially expressed genes (DEGs) between diagnosis and relapse in Cohort I. Unsupervised clustering yielded three distinct DEG groups: group A, B and C genes that were predominantly (88%) down-regulated, divergently regulated, or predominantly (65%) up-regulated, respectively, upon relapse. The expression pattern of all DEGs separated the patients into two clusters, most robustly by Group B genes. Interestingly, the majority of DEGs did not associate with changes in gene promoter methylation. Similar patterns were observed in Cohort II. We used Binding Analysis for Regulation of Transcription (BART) to identify transcriptional regulators (TRs) that potentially regulated the DEGs not associated with DNA methylation changes, and assessed the differential expression of identified TRs during disease progression. PU.1 was identified as a potential TR for Group A genes and was down-regulated upon relapse. GATA1 and TAL1 were identified as regulating Group B genes and were up-regulated in patient cluster1 and down-regulated in cluster2, consistent with the expression pattern of Group B genes. RBBP5 was a top predicted TR for Group C genes and was up-regulated upon relapse. We next validated the potential functionality of those predicted factors. In NSG mice transplanted with a human AML specimen, TAL1 and GATA1 were downregulated in AML cells collected four weeks after chemotherapy treatment, and were inferred as TRs for the down-regulated genes, similar to the patient data. PU.1 was inferred as regulating the up-regulated genes. Furthermore, we found that the level of differential expression of TAL1, GATA1, and PU.1 in each patient specimen associated with the correlation of DEG profiles between the patient specimen and TR perturbation in human-derived hematopoietic cell lines. Our results support the possibility that in some AML patients, TRs with roles in hematopoiesis and leukemia might contribute to disease relapse. Further mechanistic studies deciphering the molecular and phenotypic events facilitated by these TRs will yield significant insight into disease biology and possible therapeutic targeting approaches in relapsed AML. Citation Format: Zhenjia Wang, Yaseswini Neelamraju, Cem Meydan, Nicholas Dunham, Jorge Gandara, Tak Lee, Subhash Prajapati, Franck Rapaport, Caroline Sheridan, Paul Zumbo, Michael Becker, Lars Bullinger, Martin Carroll, Richard D’Andrea, Richard Dillon, Ross Levine, Christopher E. Mason, Ari Melnick, Donna Neuberg, Stefan Bekiranov, Chongzhi Zang, Francine E. Garrett-Bakelman. Gene expression profiles reveal distinct regulatory activities of transcription factors GATA1 and TAL1 upon AML relapse [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3155.

Inborn errors of human IFN-γ-dependent macrophagic immunity underlie mycobacterial diseases, whereas inborn errors of IFN-α/β-dependent intrinsic immunity underlie viral diseases. Both types of IFNs induce the transcription factor IRF1. We describe unrelated children with inherited complete IRF1 deficiency and early-onset, multiple, life-threatening diseases caused by weakly virulent mycobacteria and related intramacrophagic pathogens. These children have no history of severe viral disease, despite exposure to many viruses, including SARS-CoV-2, which is life-threatening in individuals with impaired IFN-α/β immunity. In leukocytes or fibroblasts stimulated in vitro, IRF1-dependent responses to IFN-γ are, both quantitatively and qualitatively, much stronger than those to IFN-α/β. Moreover, IRF1-deficient mononuclear phagocytes do not control mycobacteria and related pathogens normally when stimulated with IFN-γ. By contrast, IFN-α/β-dependent intrinsic immunity to nine viruses, including SARS-CoV-2, is almost normal in IRF1-deficient fibroblasts. Human IRF1 is essential for IFN-γ-dependent macrophagic immunity to mycobacteria, but largely redundant for IFN-α/β-dependent antiviral immunity.

Abstract The purpose of this study is to identify key regulatory pathways that potentially drive abnormal gene expression program in relapsed Acute Myeloid Leukemia (AML) patients, by integrative computational analyses on multi-omics molecular profiles. Relapsed AML remains a clinical challenge. Epigenetic heterogeneity may contribute to transcriptional dysregulation and disease progression in AML. However, what specific transcriptional programs and potential regulatory mechanisms contribute to disease relapse are not yet well understood. To characterize the global transcriptional landscapes in relapsed AML, we integrated genomics data from two cohorts of matched diagnosis and relapse patient specimens. We identified 5,416 differentially expressed genes (DEGs) between diagnosis and relapse in Cohort I. Unsupervised clustering yielded three distinct DEG groups: group A, B and C genes that were predominantly (88%) down-regulated, divergently regulated, or predominantly (65%) up-regulated, respectively, upon relapse. The expression pattern of all DEGs separated the patients into two clusters, most robustly by Group B genes. Interestingly, the majority of DEGs did not associate with changes in gene promoter methylation. Similar patterns were observed in Cohort II. We used Binding Analysis for Regulation of Transcription (BART) to identify transcriptional regulators (TRs) that potentially regulated the DEGs not associated with DNA methylation changes, and assessed the differential expression of identified TRs during disease progression. PU.1 was identified as a potential TR for Group A genes and was down-regulated upon relapse. GATA1 and TAL1 were identified as regulating Group B genes and were up-regulated in patient cluster1 and down-regulated in cluster2, consistent with the expression pattern of Group B genes. RBBP5 was a top predicted TR for Group C genes and was up-regulated upon relapse. We next validated the potential functionality of those predicted factors. In NSG mice transplanted with a human AML specimen, TAL1 and GATA1 were downregulated in AML cells collected four weeks after chemotherapy treatment, and were inferred as TRs for the down-regulated genes, similar to the patient data. PU.1 was inferred as regulating the up-regulated genes. Furthermore, we found that the level of differential expression of TAL1, GATA1, and PU.1 in each patient specimen associated with the correlation of DEG profiles between the patient specimen and TR perturbation in human-derived hematopoietic cell lines. Our results support the possibility that in some AML patients, TRs with roles in hematopoiesis and leukemia might contribute to disease relapse. Further mechanistic studies deciphering the molecular and phenotypic events facilitated by these TRs will yield significant insight into disease biology and possible therapeutic targeting approaches in relapsed AML. Citation Format: Zhenjia Wang, Yaseswini Neelamraju, Cem Meydan, Nicholas Dunham, Jorge Gandara, Tak Lee, Subhash Prajapati, Franck Rapaport, Caroline Sheridan, Paul Zumbo, Michael Becker, Lars Bullinger, Martin Carroll, Richard D’Andrea, Richard Dillon, Ross Levine, Christopher E. Mason, Ari Melnick, Donna Neuberg, Stefan Bekiranov, Chongzhi Zang, Francine E. Garrett-Bakelman. Gene expression profiles reveal distinct regulatory activities of transcription factors GATA1 and TAL1 upon AML relapse [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3155.

The molecular basis of interindividual clinical variability upon infection with Staphylococcus aureus is unclear. We describe patients with haploinsufficiency for the linear deubiquitinase OTULIN, encoded by a gene on chromosome 5p. Patients suffer from episodes of life-threatening necrosis, typically triggered by S. aureus infection. The disorder is phenocopied in patients with the 5p− (Cri-du-Chat) chromosomal deletion syndrome. OTULIN haploinsufficiency causes an accumulation of linear ubiquitin in dermal fibroblasts, but tumor necrosis factor receptor–mediated nuclear factor κB signaling remains intact. Blood leukocyte subsets are unaffected. The OTULIN-dependent accumulation of caveolin-1 in dermal fibroblasts, but not leukocytes, facilitates the cytotoxic damage inflicted by the staphylococcal virulence factor α-toxin. Naturally elicited antibodies against α-toxin contribute to incomplete clinical penetrance. Human OTULIN haploinsufficiency underlies life-threatening staphylococcal disease by disrupting cell-intrinsic immunity to α-toxin in nonleukocytic cells.

Patients with inherited CARMIL2 or CD28 deficiency have defective T cell CD28 signaling, but their immunological and clinical phenotypes remain largely unknown. We show that only one of three CARMIL2 isoforms is produced and functional across leukocyte subsets. Tested mutant CARMIL2 alleles from 89 patients and 52 families impair canonical NF-κB but not AP-1 and NFAT activation in T cells stimulated via CD28. Like CD28-deficient patients, CARMIL2-deficient patients display recalcitrant warts and low blood counts of CD4+ and CD8+ memory T cells and CD4+ TREGs. Unlike CD28-deficient patients, they have low counts of NK cells and memory B cells, and their antibody responses are weak. CARMIL2 deficiency is fully penetrant by the age of 10 yr and is characterized by numerous infections, EBV+ smooth muscle tumors, and mucocutaneous inflammation, including inflammatory bowel disease. Patients with somatic reversions of a mutant allele in CD4+ T cells have milder phenotypes. Our study suggests that CARMIL2 governs immunological pathways beyond CD28.

Most of cell-cell interactions and crosstalks are mediated by ligand-receptor interactions. The advent of single-cell RNA-sequencing (scRNA-seq) techniques has enabled characterizing tissue heterogeneity at single-cell level. Over the past recent years, several methods have been developed to study ligand-receptor interactions at cell type level using scRNA-seq data. However, there is still no easy way to query the activity of a specific user-defined signaling pathway in a targeted way or map the interactions of the same subunit with different ligands as part of different receptor complexes. Here, we present DiSiR, a fast and easy-to-use permutation-based software framework to investigate how individual cells are interacting with each other by analyzing signaling pathways of multi-subunit ligand-activated receptors from scRNA-seq data, not only for available curated databases of ligand-receptor interactions, but also for interactions that are not listed in these databases. We show that, when utilized to infer melanoma disease map on a gold-standard dataset, DiSiR outperforms other well-known permutation-based methods, e.g., CellPhoneDB and ICELLNET. To demonstrate DiSiR’s utility in exploring data and generating biologically relevant hypotheses, we apply it to COVID lung and rheumatoid arthritis (RA) synovium scRNA-seq data and highlight potential differences between inflammatory pathways at cell type level for control vs. disease samples.

Background Natural killer (NK) cell can serve as an effective anti-cancer treatment,1,2 and enhancing NK function has been shown to enhance patient outcomes.1,2 Therefore, insight into NK cell states and subtypes may lead to new treatment options. Initial characterization of NK cells relied on flow cytometry with surface markers dividing NK cells into less mature CD56bright NKs and more mature CD56dim NKs.4 More recently, single-cell RNAseq profiling has enabled deeper characterization and revealed three novel subtypes: cytokine-induced memory-like (CIML), adaptive, low ribosomal, and type I IFN responding NKs, which enhanced the previously known CD56bright, CD56dim, and CD56dim CD57+ subtypes.5 Here, we extend this single cell subtyping by building a cancer-focused NK cell Atlas that integrates 25 public datasets from multiple types of cancers and delineates both the subtypes and states of the NK cells. Methods Single cell sequencing datasets were downloaded from the studies listed in [table 1]. NK cells were identified using the HaiTam cell type prediction algorithm v1.6 Harmony v0.1.07 was used for batch correction and ACTIONet v3.0.08 was used for data integration and cell state identification. Cell state abundance comparisons were performed using 1-way ANOVA with Dunnett's post hoc test. Results We generated an Atlas of 89,704 NK cells from 281 donors in 21 cancer focused studies, 3 studies using healthy donors, and 1 study of ulcerative colitis [table 1]. We identified 12 unique NK cellular states in our Atlas [figure 1]. Some states recapitulated known NK subtypes such as CIMLs and type 1 IFN responders. By contrast, CD56dim NKs were represented by 2 cellular states and CD56bright NKs were represented by 3 states. We found that one of these CD56bright states is more abundant in blood from renal cell cancer patients than in blood from healthy donors (2.1-fold change; p < 0.02). Compared to other CD56bright states, this overrepresented state expresses higher levels of the cytotoxic gene GZMK and of migratory markers CD44, CXCR3 and SELL. Conclusions Our Atlas describes 12 NK cell states reflecting maturation, activation, and exhaustion in cancer. These states provide a framework for assessing co-expression of targets for NK modulators and for understanding the effects of treatments on NK cells. References Chu J, Gao F, Yan M, Zhao S, Yan Z, Shi B, Liu Y. Natural killer cells: a promising immunotherapy for cancer. eBioMedicine 2020;59:102975. Suen W, Lee W, Leung K, Pan X, Li G. Natural Killer Cell-Based Cancer Immunotherapy: A Review on 10 Years Completed Clinical Trials. 2018;36:431–457. Abou-El-Enein M, Bauer G, Medcalf N, Volk H, Reinke P. Putting a price tag on novel autologous cellular therapies. Cytotherapy 2016;18:1056–1061. Moretta L. Dissecting CD56dim human NK cells. Blood 2010; 116:3689–3691. Smith L, Kennedy P, Stacey K, Worboys J, Yarwood A, Seo A, Solloa W, Mistretta B, Chatterjee S, Gunaratne P, Allette K, Wang Y, Smith M, Sebra R, Mace E, Horowitz A, Thomson W, Martin P, Eyre S, Davis D. Diversity of peripheral blood human NK cells identified by single-cell RNA sequencing. Blood Adv 2020;4:1388–1406. Talk2data [https://talk2data.bioturing.com/predict] Korsunsky I, Millard N, Fan J, Slowikowski K, Zhang F, Wei K, Baglaenko Y, Brenner M, Loh P, Raychaudhuri S. Fast, sensitive and accurate integration of single-cell data with Harmony. 2019;16:1289–1296. Mohammadi S, Velderrain J, Kellis M. A multiresolution framework to characterize single-cell state landscapes. Nature Communications 2020;11:5399.

Human inborn errors of IFN-γ underlie mycobacterial disease, due to insufficient IFN-γ production by lymphoid cells, impaired myeloid cell responses to this cytokine, or both. We report four patients from two unrelated kindreds with intermittent monocytosis and mycobacterial disease, including bacillus Calmette-Guérin-osis and disseminated tuberculosis, and without any known inborn error of IFN-γ. The patients are homozygous for ZNFX1 variants (p.S959* and p.E1606Rfs*10) predicted to be loss of function (pLOF). There are no subjects homozygous for pLOF variants in public databases. ZNFX1 is a conserved and broadly expressed helicase, but its biology remains largely unknown. It is thought to act as a viral double-stranded RNA sensor in mice, but these patients do not suffer from severe viral illnesses. We analyze its subcellular localization upon overexpression in A549 and HeLa cell lines and upon stimulation of THP1 and fibroblastic cell lines. We find that this cytoplasmic protein can be recruited to or even induce stress granules. The endogenous ZNFX1 protein in cell lines of the patient homozygous for the p.E1606Rfs*10 variant is truncated, whereas ZNFX1 expression is abolished in cell lines from the patients with the p.S959* variant. Lymphocyte subsets are present at normal frequencies in these patients and produce IFN-γ normally. The hematopoietic and nonhematopoietic cells of the patients tested respond normally to IFN-γ. Our results indicate that human ZNFX1 is associated with stress granules and essential for both monocyte homeostasis and protective immunity to mycobacteria.

Purpose Germline heterozygous mutations of GATA2 underlie a variety of hematological and clinical phenotypes. The genetic, immunological, and clinical features of GATA2-deficient patients with mycobacterial diseases in the familial context remain largely unknown. Methods We enrolled 15 GATA2 index cases referred for mycobacterial disease. We describe their genetic and clinical features including their relatives. Results We identified 12 heterozygous GATA2 mutations, two of which had not been reported. Eight of these mutations were loss-of-function, and four were hypomorphic. None was dominant-negative in vitro, and the GATA2 locus was found to be subject to purifying selection, strongly suggesting a mechanism of haploinsufficiency. Three relatives of index cases had mycobacterial disease and were also heterozygous, resulting in 18 patients in total. Mycobacterial infection was the first clinical manifestation in 11 patients, at a mean age of 22.5 years (range: 12 to 42 years). Most patients also suffered from other infections, monocytopenia, or myelodysplasia. Strikingly, the clinical penetrance was incomplete (32.9% by age 40 years), as 16 heterozygous relatives aged between 6 and 78 years, including 4 older than 60 years, were completely asymptomatic. Conclusion Clinical penetrance for mycobacterial disease was found to be similar to other GATA2 deficiency-related manifestations. These observations suggest that other mechanisms contribute to the phenotypic expression of GATA2 deficiency. A diagnosis of autosomal dominant GATA2 deficiency should be considered in patients with mycobacterial infections and/or other GATA2 deficiency-related phenotypes at any age in life. Moreover, all direct relatives should be genotyped at the GATA2 locus.

Purpose: Biomarkers of response and resistance to FLT3 tyrosine kinase inhibitors (TKI) are still emerging, and optimal clinical combinations remain unclear. The purpose of this study is to identify co-occurring mutations that influence clinical response to the novel FLT3 inhibitor pexidartinib (PLX3397). Experimental Design: We performed targeted sequencing of pretreatment blasts from 29 patients with FLT3 internal tandem duplication (ITD) mutations treated on the phase I/II trial of pexidartinib in relapsed/refractory FLT3-ITD+ acute myeloid leukemia (AML). We sequenced 37 samples from 29 patients with available material, including 8 responders and 21 non-responders treated at or above the recommended phase II dose of 3,000 mg. Results: Consistent with other studies, we identified mutations in NRAS, TP53, IDH2, and a variety of epigenetic and transcriptional regulators only in non-responders. Among the most frequently mutated genes in non-responders was Cyclin D3 (CCND3). A total of 3 individual mutations in CCND3 (Q276*, S264R, and T283A) were identified in 2 of 21 non-responders (one patient had both Q276* and S264R). No CCND3 mutations were found in pexidartinib responders. Expression of the Q276* and T283A mutations in FLT3-ITD MV4;11 cells conferred resistance to apoptosis, decreased cell-cycle arrest, and increased proliferation in the presence of pexidartinib and other FLT3 inhibitors. Inhibition of CDK4/6 activity in CCND3 mutant MV4;11 cells restored pexidartinib-induced cell-cycle arrest but not apoptosis. Conclusions: Mutations in CCND3, a gene not commonly mutated in AML, are a novel cause of clinical primary resistance to FLT3 inhibitors in AML and may have sensitivity to CDK4/6 inhibition.